“徐光启全集”由著名学者和徐光启研究专家朱维铮、李天纲主编，此次整理在原来上海古籍出版社《徐光启集》、《徐光启著译集》、《农政全书》等书的基础上增加了许多近年海内外新发现的佚著佚文，吸收了学界*新的研究成果。其中《毛诗六帖讲意》、《徐氏庖言》、《测量法义》、《灵言蠡勺》等十多种专书是首次点校排印出版，对于徐光启和中西文化交流史的研究具有重要的推动作用；标点整理了完整的利玛窦、徐光启合译本《几何原本》，由于此书的历史地位和作为现代科学翻译的开先河之作，此次整理出版具有非常特殊的意义；另有在1960年代原编徐光启文集和年谱的基础上增加和更新三分之一以上内容的新编《徐光启诗文集》、《增补徐光启年谱》，将成为徐光启研究的基础资料。　本书（《几何原本》）为全集之一册，是利玛窦和徐光启合译的古希腊数学家欧几里得的名著，是该著最早的中文译本，在中国科技史和中外文化交流史上具有非常重要的影响。

Since the 1970s， Science Press has published more than thirty volumes in its series Monographs in Computational Methods. This series was established and led by the late academician， Feng Kang， the founding director of the Computing Center of the Chinese Academy of Sciences. The monograph series has provided timely information of the frontier directions and latest research results in computational mathematics. It has had great impact on young scientists and the entire research community， and has played a very important role in the development of computational mathematics in China.To cope with these new scientific developments， the Ministry of Education of the People's Republic of China in 1998 combined several subjects， such as computational mathematics， numerical algorithms， information science， and operations research and optimal control， into a new discipline called Information and Computational Science. As a result， Science Press also reorganized the editorial board of the monograph series and changed its name to Series in Information and Computational Science. The first editorial board meeting was held in Beijing in September 2004， and it discussed the new objectives， and the directions and contents of the new monograph series.The aim of the new series is to present the state of the art in Information and Computational Science to senior undergraduate and graduate students， as well as to scientists working in these fields. Hence， the series will provide concrete and systematic expositions of the advances in information and computational science， encompassing also related interdisciplinary developments.I would like to thank the previous editorial board members and assistants， and all the mathematicians who have contributed significantly to the monograph series on Computational Methods. As a result of their contributions the monograph series achieved an outstanding reputation in the community. I sincerely wish that we will extend this support to the new Series in Information and Computational Science， so that the new series can equally enhance the scientific development in information and computational science in this century.

图论在现代科学技术中有着广泛的应用，如网络设计、计算机科学、信息科学、密码学、DNA基因谱的确定和计数、工业生产和企业管理中的优化方法等。图论与结构化学的交叉形成了化学图论，因此，化学图论是图论的重要分支之一，主要研究与化学分子图的物理、化学性质密切相关的拓扑不变量和拓扑性质，在预测、合**的化合物与新的药品方面有着很重要的应用。《Merrifield-Simmons指标和Hosoya指标的研究及应用》主要研究化学图论中两个非常重要的拓扑指标Merrifield-Simmons指标和Hosoya指标，系统阐述这个研究领域的理论与应用研究成果，主要包括树形苯环系统、单圈图、双圈图及多圈图等图族的Merrificld-Simmons指标和Hosoya指标的计算公式或上、下界，聚苯环系统的Hosoya指标的计算公式，以及多圈图Hosoya指标的上、下界。《Merrifield-Simmons指标和Hosoya指标的研究及应用》可供从事化学图论研究和图论教学的广大教师、学生阅读与参考。

《周期Sylvester矩阵方程的解及其应用》讨论周期Sylvester矩阵方程的求解及其在控制理论和工程中的应用问题，内容包括相关的理论基础、设计算法和应用。《周期Sylvester矩阵方程的解及其应用》是作者近些年来在周期矩阵与鲁棒控制领域研究与实践工作的总结与提炼。《周期Sylvester矩阵方程的解及其应用》共5章，第1章阐述了相关周期矩阵和线性周期系统的研究背景、研究进展及存在的问题；第2章介绍了周期Sylvester矩阵方程的迭代求解算法及其在理论和实践中的应用；第3章聚焦于广义周期耦合Sylvester矩阵方程的求解方法；第4章利用周期PD反馈对二阶线性周期系统进行鲁棒极点配置；第5章给出了具有时变状态和输入维数的线性周期系统的极点配置问题的解决方案。

《矩阵论入门》共5章，第1章是简要的预备知识，包括线性代数（矩阵消元法、置换矩阵、Schmidt正交化、镜面反射、分块矩阵的乘法），以及一元多项式的互素与整除；第2章是矩阵的各种分解式，也是对大学阶段线性代数的复习与提升，包括正规矩阵与酉相似、矩阵分解式、Moore-Penrose广义逆以及Hermite半正定矩阵的幂表达定理；第3章是较为完整的线性变换理论，也是《矩阵论入门》的理论核心，包括若干关于线性变换与矩阵的一一对应定理、根子空间分解定理以及Jordan标准形的简要现代处理、线性空间与线性映射（矩阵）的张量积与外幂；第4章是矩阵分析，包括向量范数及其诱导的矩阵范数、矩阵函数概要、特征值的估计（几个圆盘定理）、非负方阵与正方阵以及三个相关的核心定理、随机矩阵。第4章与第2章一起构成工科矩阵理论的核心内容，技巧性强且具有重要的应用背景。第5章收集了有关矩阵理论应用的一些关键词，方便读者搜索应用。《矩阵论入门》配备部分具有一定难度的题目（标记*），这些题目也是矩阵理论的重要内容；基于这一考量，对部分较难的题目给出了提示或解答。　《矩阵论入门》内容的编排，遵循由浅入深原则，特别强调逻辑一致性；在重视技巧性的同时，适度强调一定的思想性。

《探索数学之美》以探索数学之美、激发学生学习兴趣为主要任务导向，从数字起源、逻辑推理、选择、几何、悖论等八个模块进行编写，从探索的角度，了解数学，走近数学，学习数学，让学生在看到数学时，不再仅仅局限于方程、函数等枯燥无味的习题。另外，《探索数学之美》也想通过对于悖论的研究和逻辑的应用，教会学生更好地将数学融入实践，用于生活。

随着物联网、数字医疗、智慧城市的兴起，时间序列数据分析变得越来越重要，持续监测和数据收集变得越来越普遍，对通过统计和机器学习技术进行时间序列分析的需求将会增长。

《微分方程数值方法——有限差分法》介绍了微分方程数值求解方法——有限差分法。内容涉及有限差分法的基本设计过程与具体的实现过程，有限差分法在工程、科学和数学问题中的应用以及MATLAB程序，涵盖了有限差分法的很多内容：常微分方程的数值解法；二阶椭圆型、二阶抛物型及二阶双曲型方程的数值算法；各种非线性偏微分方程以及非线性偏微分方程组的数值方法； 数值积分与数值微分在偏微分方程求解过程中的应用等。《微分方程数值方法——有限差分法》的一大特色是给出大量的应用实例并附MATLAB程序。

The study of graph theory started over two hundreds years ago. The earliest known paper is due to Euler（1736） about the seven bridges of Korugsberg. Since 1960s， graph theory has developed very fast and numerous results on graph theory sprung forth. There are many nice and celebrated problems in graph theory， such as Hamiltonian problem， four-color problem， Chinese postman problem， etc. Moreover， graph theory is widely applied in chemistry， computer science， biology and other disciplines. As a subfield in discrete mathematics， graph theory has attracted much attention from all perspectives.All graphs are considered only finite， simple， undirected graphs with no loops and no multiple edges. Let G be a graph. The Hamiltonian cycle problem is one of the most well-known problems in graph theory. A cycle which contains every vertex of G is called a Hamiltonian cycle. A cycle is called a chorded cycle if this cycle contains at least one chord. A k-factor in a graph G is a spanning k-regular subgraph of G， where k is a positive integer. There exists many interesting results about the existence of k-factor， by applying Tuttes Theorem， however， we mainly focus on the existence of 2-factor throughout this thesis. Clearly， a Hamiltonian cycle is a 2-factor with exactly one component. From this point of view， it is a more complex procedure to find the condition to ensure the existence of 2-factor in a given graph. The most usual technique to resolve 2-factor problems is to find a minimal packing and then extend it to a required 2-factor.The book is concerned with structural invariants for packing cycles in a graph and partitions of a graph into cycles， i.e.， finding a prescribed number of vertex-disjoint cycles and vertex-partitions into a prescribed number of cycles in graphs. It is well-known that the problem of determining whether a given graph has such partitions or not， is NP-complete. Therefore， many researchers have investigated degree conditions for packing and partitioning. This book mainly focuses on the following invariants for such problems： minimum degree， average degree （also extremal function）， degree sum of independent vertices and the order condition with minimum degree.

This book is intended to have three roles and to serve three associated audiences： anintroductory text on Bayesian inference starting from first principles， a graduate text oneffective current approaches to Bayesian modeling and computation in statistics and relatedfields， and a handbook of Bayesian methods in applied statistics for general users of andresearchers in applied statistics. Although introductory in its early sections， the book isdefinitely not elementary in the sense of a first text in statistics. The mathematics usedin our book is basic probability and statistics， elementary calculus， and linear algebra. Areview of probability notation is given in Chapter 1 along with a more detailed list of topicsassumed to have been studied. The practical orientation of the book means that the reader'sprevious experience in probability， statistics， and linear algebra should ideally have includedstrong computational components.To write an introductory text alone would leave many readers with only a taste of theconceptual elements but no guidance for venturing into genuine practical applications， be-yond those where Bayesian methods agree essentially with standard non-Bayesian analyses.On the other hand， we feel it would be a mistake to present the advanced methods with-out first introducing the basic concepts from our data-analytic perspective. Furthermore，due to the nature of applied statistics， a text on current Bayesian methodology would beincomplete without a variety of worked examples drawn from real applications. To avoidcluttering the main narrative， there are bibliographic notes at the end of each chapter andreferences at the end of the book.